পাবলিক ইন্টারফেস ConfigProtoOrBuilder
| পরিচিত পরোক্ষ উপশ্রেণী |
পাবলিক পদ্ধতি
| বিমূর্ত বুলিয়ান | ডিভাইস কাউন্ট রয়েছে (স্ট্রিং কী) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. |
| বিমূর্ত বুলিয়ান | getAllowSoftPlacement () Whether soft placement is allowed. |
| বিমূর্ত ClusterDef | getClusterDef () Optional list of all workers to use in this session. |
| বিমূর্ত ClusterDefOrBuilder | getClusterDefOrBuilder () Optional list of all workers to use in this session. |
| বিমূর্ত মানচিত্র <স্ট্রিং, পূর্ণসংখ্যা> | getDeviceCount () পরিবর্তে getDeviceCountMap() ব্যবহার করুন। |
| বিমূর্ত int | getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. |
| বিমূর্ত মানচিত্র <স্ট্রিং, পূর্ণসংখ্যা> | getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. |
| বিমূর্ত int | getDeviceCountOrDefault (স্ট্রিং কী, int defaultValue) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. |
| বিমূর্ত int | getDeviceCountOrThrow (স্ট্রিং কী) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. |
| বিমূর্ত স্ট্রিং | getDeviceFilters (int সূচক) When any filters are present sessions will ignore all devices which do not match the filters. |
| বিমূর্ত com.google.protobuf.ByteString | getDeviceFiltersBytes (int সূচক) When any filters are present sessions will ignore all devices which do not match the filters. |
| বিমূর্ত int | getDeviceFiltersCount () When any filters are present sessions will ignore all devices which do not match the filters. |
| বিমূর্ত তালিকা<স্ট্রিং> | getDeviceFiltersList () When any filters are present sessions will ignore all devices which do not match the filters. |
| বিমূর্ত ConfigProto.Experimental | পরীক্ষামূলক () .tensorflow.ConfigProto.Experimental experimental = 16; |
| বিমূর্ত ConfigProto.ExperimentalOrBuilder | GetExperimentalOrBuilder () .tensorflow.ConfigProto.Experimental experimental = 16; |
| বিমূর্ত GPUOptions | getGpuOptions () Options that apply to all GPUs. |
| বিমূর্ত GPUOptionsOrBuilder | getGpuOptionsOrBuilder () Options that apply to all GPUs. |
| বিমূর্ত GraphOptions | GetGraphOptions () Options that apply to all graphs. |
| বিমূর্ত GraphOptionsOrBuilder | getGraphOptionsOrBuilder () Options that apply to all graphs. |
| বিমূর্ত int | GetInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process. |
| বিমূর্ত int | GetIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads. |
| বিমূর্ত বুলিয়ান | getIsolateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions. |
| বিমূর্ত বুলিয়ান | getLogDevicePlacement () Whether device placements should be logged. |
| বিমূর্ত দীর্ঘ | getOperationTimeoutInMs () Global timeout for all blocking operations in this session. |
| বিমূর্ত int | গেট প্লেসমেন্ট পিরিয়ড () Assignment of Nodes to Devices is recomputed every placement_period steps until the system warms up (at which point the recomputation typically slows down automatically). |
| বিমূর্ত RPCOptions | getRpcOptions () Options that apply when this session uses the distributed runtime. |
| বিমূর্ত RPCOptionsOrBuilder | getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime. |
| বিমূর্ত ThreadPoolOptionProto | getSessionInterOpThreadPool (int সূচক) This option is experimental - it may be replaced with a different mechanism in the future. |
| বিমূর্ত int | getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future. |
| বিমূর্ত তালিকা< ThreadPoolOptionProto > | getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future. |
| বিমূর্ত ThreadPoolOptionProtoOrBuilder | getSessionInterOpThreadPoolOrBuilder (int সূচক) This option is experimental - it may be replaced with a different mechanism in the future. |
| বিমূর্ত তালিকা<? ThreadPoolOptionProtoOrBuilder > প্রসারিত করে | getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future. |
| বিমূর্ত বুলিয়ান | getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster. |
| বিমূর্ত বুলিয়ান | getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads. |
| বিমূর্ত বুলিয়ান | hasClusterDef () Optional list of all workers to use in this session. |
| বিমূর্ত বুলিয়ান | আছে পরীক্ষামূলক () .tensorflow.ConfigProto.Experimental experimental = 16; |
| বিমূর্ত বুলিয়ান | hasGpuOptions () Options that apply to all GPUs. |
| বিমূর্ত বুলিয়ান | আছে গ্রাফ অপশন () Options that apply to all graphs. |
| বিমূর্ত বুলিয়ান | hasRpcOptions () Options that apply when this session uses the distributed runtime. |
পাবলিক পদ্ধতি
সর্বজনীন বিমূর্ত বুলিয়ানে রয়েছে ডিভাইস কাউন্ট (স্ট্রিং কী)
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1; সর্বজনীন বিমূর্ত বুলিয়ান getAllowSoftPlacement ()
Whether soft placement is allowed. If allow_soft_placement is true, an op will be placed on CPU if 1. there's no GPU implementation for the OP or 2. no GPU devices are known or registered or 3. need to co-locate with reftype input(s) which are from CPU.
bool allow_soft_placement = 7; সর্বজনীন বিমূর্ত ClusterDef getClusterDef ()
Optional list of all workers to use in this session.
.tensorflow.ClusterDef cluster_def = 14; সর্বজনীন বিমূর্ত ClusterDefOrBuilder getClusterDefOrBuilder ()
Optional list of all workers to use in this session.
.tensorflow.ClusterDef cluster_def = 14; সর্বজনীন বিমূর্ত মানচিত্র<স্ট্রিং, পূর্ণসংখ্যা> getDeviceCount ()
পরিবর্তে getDeviceCountMap() ব্যবহার করুন।
পাবলিক বিমূর্ত int getDeviceCountCount ()
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1; সর্বজনীন বিমূর্ত মানচিত্র<স্ট্রিং, পূর্ণসংখ্যা> getDeviceCountMap ()
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1; সর্বজনীন বিমূর্ত int getDeviceCountOrDefault (স্ট্রিং কী, int defaultValue)
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1;পাবলিক বিমূর্ত int getDeviceCountOrThrow (স্ট্রিং কী)
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1; সর্বজনীন বিমূর্ত স্ট্রিং getDeviceFilters (int সূচক)
When any filters are present sessions will ignore all devices which do not match the filters. Each filter can be partially specified, e.g. "/job:ps" "/job:worker/replica:3", etc.
repeated string device_filters = 4; সর্বজনীন বিমূর্ত com.google.protobuf.ByteString getDeviceFiltersBytes (int index)
When any filters are present sessions will ignore all devices which do not match the filters. Each filter can be partially specified, e.g. "/job:ps" "/job:worker/replica:3", etc.
repeated string device_filters = 4; পাবলিক বিমূর্ত int getDeviceFiltersCount ()
When any filters are present sessions will ignore all devices which do not match the filters. Each filter can be partially specified, e.g. "/job:ps" "/job:worker/replica:3", etc.
repeated string device_filters = 4; সর্বজনীন বিমূর্ত তালিকা<String> getDeviceFiltersList ()
When any filters are present sessions will ignore all devices which do not match the filters. Each filter can be partially specified, e.g. "/job:ps" "/job:worker/replica:3", etc.
repeated string device_filters = 4; সর্বজনীন বিমূর্ত ConfigProto.পরীক্ষামূলক getExperimental ()
.tensorflow.ConfigProto.Experimental experimental = 16;
সর্বজনীন বিমূর্ত ConfigProto.ExperimentalOrBuilder getExperimentalOrBuilder ()
.tensorflow.ConfigProto.Experimental experimental = 16;
সর্বজনীন বিমূর্ত GPUOptions getGpuOptions ()
Options that apply to all GPUs.
.tensorflow.GPUOptions gpu_options = 6; সর্বজনীন বিমূর্ত GPUOptionsOrBuilder getGpuOptionsOrBuilder ()
Options that apply to all GPUs.
.tensorflow.GPUOptions gpu_options = 6; সর্বজনীন বিমূর্ত GraphOptions getGraphOptions ()
Options that apply to all graphs.
.tensorflow.GraphOptions graph_options = 10; সর্বজনীন বিমূর্ত GraphOptionsOrBuilder getGraphOptionsOrBuilder ()
Options that apply to all graphs.
.tensorflow.GraphOptions graph_options = 10; সর্বজনীন বিমূর্ত int getInterOpParallelismThreads ()
Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process. 0 means the system picks an appropriate number. Negative means all operations are performed in caller's thread. Note that the first Session created in the process sets the number of threads for all future sessions unless use_per_session_threads is true or session_inter_op_thread_pool is configured.
int32 inter_op_parallelism_threads = 5; সর্বজনীন বিমূর্ত int getIntraOpParallelismThreads ()
The execution of an individual op (for some op types) can be
parallelized on a pool of intra_op_parallelism_threads.
0 means the system picks an appropriate number.
If you create an ordinary session, e.g., from Python or C++,
then there is exactly one intra op thread pool per process.
The first session created determines the number of threads in this pool.
All subsequent sessions reuse/share this one global pool.
There are notable exceptions to the default behavior describe above:
1. There is an environment variable for overriding this thread pool,
named TF_OVERRIDE_GLOBAL_THREADPOOL.
2. When connecting to a server, such as a remote `tf.train.Server`
instance, then this option will be ignored altogether.
int32 intra_op_parallelism_threads = 2; সর্বজনীন বিমূর্ত বুলিয়ান getIsolateSessionState ()
If true, any resources such as Variables used in the session will not be shared with other sessions. However, when clusterspec propagation is enabled, this field is ignored and sessions are always isolated.
bool isolate_session_state = 15; সর্বজনীন বিমূর্ত বুলিয়ান getLogDevicePlacement ()
Whether device placements should be logged.
bool log_device_placement = 8; সর্বজনীন বিমূর্ত দীর্ঘ getOperationTimeoutInMs ()
Global timeout for all blocking operations in this session. If non-zero, and not overridden on a per-operation basis, this value will be used as the deadline for all blocking operations.
int64 operation_timeout_in_ms = 11; পাবলিক বিমূর্ত int getPlacementPeriod ()
Assignment of Nodes to Devices is recomputed every placement_period steps until the system warms up (at which point the recomputation typically slows down automatically).
int32 placement_period = 3; সর্বজনীন বিমূর্ত RPCOptions getRpcOptions ()
Options that apply when this session uses the distributed runtime.
.tensorflow.RPCOptions rpc_options = 13; সর্বজনীন বিমূর্ত RPCOptionsOrBuilder getRpcOptionsOrBuilder ()
Options that apply when this session uses the distributed runtime.
.tensorflow.RPCOptions rpc_options = 13; সর্বজনীন বিমূর্ত ThreadPoolOptionProto getSessionInterOpThreadPool (int সূচক)
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12; পাবলিক বিমূর্ত int getSessionInterOpThreadPoolCount ()
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12; সর্বজনীন বিমূর্ত তালিকা< ThreadPoolOptionProto > getSessionInterOpThreadPoolList ()
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12; সর্বজনীন বিমূর্ত ThreadPoolOptionProtoOrBuilder getSessionInterOpThreadPoolOrBuilder (int সূচক)
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12; সর্বজনীন বিমূর্ত তালিকা<? ThreadPoolOptionProtoOrBuilder > getSessionInterOpThreadPoolOrBuilderList () প্রসারিত করে
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12; পাবলিক বিমূর্ত বুলিয়ান getShareClusterDevicesInSession ()
When true, WorkerSessions are created with device attributes from the full cluster. This is helpful when a worker wants to partition a graph (for example during a PartitionedCallOp).
bool share_cluster_devices_in_session = 17; সর্বজনীন বিমূর্ত বুলিয়ান getUsePerSessionThreads ()
If true, use a new set of threads for this session rather than the global pool of threads. Only supported by direct sessions. If false, use the global threads created by the first session, or the per-session thread pools configured by session_inter_op_thread_pool. This option is deprecated. The same effect can be achieved by setting session_inter_op_thread_pool to have one element, whose num_threads equals inter_op_parallelism_threads.
bool use_per_session_threads = 9; পাবলিক বিমূর্ত বুলিয়ান hasClusterDef ()
Optional list of all workers to use in this session.
.tensorflow.ClusterDef cluster_def = 14; পাবলিক বিমূর্ত বুলিয়ান আছে এক্সপেরিমেন্টাল ()
.tensorflow.ConfigProto.Experimental experimental = 16;
সর্বজনীন বিমূর্ত বুলিয়ান hasGpuOptions ()
Options that apply to all GPUs.
.tensorflow.GPUOptions gpu_options = 6; সর্বজনীন বিমূর্ত বুলিয়ান আছে গ্রাফ অপশন ()
Options that apply to all graphs.
.tensorflow.GraphOptions graph_options = 10; পাবলিক বিমূর্ত বুলিয়ান hasRpcOptions ()
Options that apply when this session uses the distributed runtime.
.tensorflow.RPCOptions rpc_options = 13;